adobe photoshop - What benefits are there to workflows using Images at 32-bits per channel?

To be clear, I'm referring to images that have a color depth of 32-bits per channel.

Has anyone ever used images this large in a workflow – other than as RAW files directly from a camera?

If so, why did you need that much depth?

What benefits are there to using 32bit color depth?

Answer

32 bit per channel is most likely a floating point image. Tough it could also be 32 bit integers but i have never seen such images. Both TIF, EXR and some proprietary film production formats can use 32 bit float per channel inside them.

There are several reasons for using higher order bit depths. First of the image might not be a photograph. It might be some scientific or cartographic data. If it is a photograph its probably a HDRI image that has much wider color gamut than normal images Also HDRI is not 0-1 range but potentially 0-quite much more than 1000 in range).

Admittedly these data orders are not really for graphics designers except maybe HDRI conditioning. The reason for using these higher order data is that you might be processing the data further.

This often comes up in 3d graphics as you want to derive real lightning conditions form your images. Reflections depend on colors that over exceed the human gamut to look proper (like the sky reflection on cars). So what you really want your images to do is encode the energy levels. Which is not possible with the kind of standard images we commonly use as they are individually exposed. But what if you want to expose things after complex computation?

It also comes up in post processing of 3d graphics where you might be doing the final computation and you need the normal to be you know normal. So you might need to have negative colors at your disposal. Images are much more than what you think sometimes people use them to compute stuff like new lightning conditions on the fly.

There are also many engineering applications where it comes up, like game development, FEM calculation. It also comes up in measurement scenarios in engineering. You might also be dong some mathematical operations like FFT or Laplace transforms and then back and you dont want too loose all that much in the process so you'd up the sample levels. This is cool if you need to do very specific noise removal

have I used 32 bit per channel floating point images?

Yes I have, I have also used 64 bit floating point images because i was getting nasty noise levels with 32 bit floats. Admittedly 32 bits is a bit overkill for most situations.

PS

Not all output formats are 8 bit, printing in certain film substrate is often 12-16 bits also movies often use higher bit depths than 8 bit. But for traditional web/ print design its not much of thing. Then again you might get asked to design film titles (at least you wish this was true).